Mining, Metallurgy & Exploration最新文献_第5页

Sustainable Water Recovery from a Hydrometallurgical Effluent Using Gas Hydrate-Based Desalination in the Presence of CO2 Nanobubbles 在二氧化碳纳米气泡存在的情况下利用气体水合物脱盐技术从湿法冶金废水中可持续地回收水资源

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-19 DOI: 10.1007/s42461-024-01046-7

Seyed Mohammad Montazeri, Georgios Kolliopoulos

{"title":"Sustainable Water Recovery from a Hydrometallurgical Effluent Using Gas Hydrate-Based Desalination in the Presence of CO2 Nanobubbles","authors":"Seyed Mohammad Montazeri, Georgios Kolliopoulos","doi":"10.1007/s42461-024-01046-7","DOIUrl":"https://doi.org/10.1007/s42461-024-01046-7","url":null,"abstract":"Hydrometallurgical processes generate large volumes of aqueous effluents, which are being treated and disposed in tailings ponds. Effluent desalination, i.e., clean water recovery for reuse in process circuits, is key to attain a zero liquid discharge future in the industry. In this study, we report on the use of hydrate-based desalination (HBD) to treat a synthesized effluent from the zinc industry. HBD is an innovative, energy-efficient, and sustainable desalination technology, capable to treat hydrometallurgical effluents to recover water in the form of gas hydrates by consuming CO2. Water recovery and total dissolved solids (TDS) removal efficiency of 42 ± 2% and 60 ± 4% were achieved in a three-stage HBD process. Further, CO2 nanobubbles (NBs) were tested as a sustainable kinetic promoter of the process. The desalination outcomes verified that CO2 NBs played a crucial role in enhancing the kinetics of the process. Specifically, the presence of CO2 NBs resulted in a notable increase in water recovery, which reached 60 ± 2%, accompanied by a TDS removal efficiency of 53 ± 1% in a three-stage HBD process.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"58 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141746027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification Support Technology for Roadways in Deep Broken Soft Rock: A Case Study 深破碎软岩中道路的分类支持技术：案例研究

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-19 DOI: 10.1007/s42461-024-01048-5

Jieyang Ma, Shihao Tu, Hongsheng Tu, Kaijun Miao, Long Tang, Hongbin Zhao, Benhuan Guo

{"title":"Classification Support Technology for Roadways in Deep Broken Soft Rock: A Case Study","authors":"Jieyang Ma, Shihao Tu, Hongsheng Tu, Kaijun Miao, Long Tang, Hongbin Zhao, Benhuan Guo","doi":"10.1007/s42461-024-01048-5","DOIUrl":"https://doi.org/10.1007/s42461-024-01048-5","url":null,"abstract":"This paper addresses the surrounding rock control problem of deep roadways in broken soft rock. The 21914 working face haulage roadway in the Zhangshuanglou coal mine was taken as a case study. The deformation characteristics and failure mechanisms of the roadway surrounding rock were analysed via theoretical analysis and numerical simulation. A classification support technology was proposed and then applied to the studied roadway. This study indicated that the high stresses, mining disturbances and mechanical properties of soft rock resulted in large deformations developed over long periods, leading to the destruction of the deep roadway in the soft rock. The failure depth of the upper goaf floor was 15.84 m, and the development radius of the plastic zone during roadway excavation was 9.55 m. The roadway deformation was positively correlated with the thickness of the interbedded fractured coal and negatively correlated with the thickness of the fractured sandy mudstone. This paper proposed a classification support technology with the main steps of surrounding rock status identification, parameter determination and graded support; the chief support measures were the addition of grout, bolts, anchor cables, steel strips, steel beams and trapezoidal sheds. The field work showed that classification support could effectively restrain the large deformation of the surrounding rock. This research can provide a reference for the stability control of other roadways under similar conditions. ","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"76 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141738002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NIR-Spectroscopy and Machine Learning Models to Pre-concentrate Copper Hosted Within Sedimentary Rocks 利用近红外光谱和机器学习模型对沉积岩中的铜矿进行预浓缩

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-12 DOI: 10.1007/s42461-024-01013-2

Samira Es-sahly, Abdelaziz Elbasbas, Khalid Naji, Brahim Lakssir, Hakim Faqir, Slimane Dadi, Reda Rabie

{"title":"NIR-Spectroscopy and Machine Learning Models to Pre-concentrate Copper Hosted Within Sedimentary Rocks","authors":"Samira Es-sahly, Abdelaziz Elbasbas, Khalid Naji, Brahim Lakssir, Hakim Faqir, Slimane Dadi, Reda Rabie","doi":"10.1007/s42461-024-01013-2","DOIUrl":"https://doi.org/10.1007/s42461-024-01013-2","url":null,"abstract":"The western part of the Moroccan Anti-Atlas comprises numerous copper occurrences hosted within various sedimentary rocks, all containing low-grade copper concentrations. This study aims to assess the feasibility of using a near-infrared (NIR) sorting system to efficiently process these low-grade resources. In essence, it involves evaluating the potential of short-wave infrared (SWIR) spectroscopy and machine learning models to classify ore fragments into waste or concentrate based on their SWIR spectral characteristics. In order to conduct this study, the SWIR reflectance of 475 rock samples from the Tizert deposit was measured. Mineralogical analysis was performed, using X-ray diffraction and scanning electron microscopy, to understand the mineralogy of the samples and its relationship to SWIR spectra. Chemical analysis was also performed to categorize samples based on their copper content. Several machine learning models, including partial least squares discriminant analysis (PLS-DA), random forest (RF), and support vector machine (SVM) were evaluated based on both lithology and copper content characteristics. Among these, PLS-DA yielded the most favorable results, achieving an 84% accuracy in lithologies classification and 90% accuracy in classifying samples based on their copper content, utilizing a 0.2% cutoff grade. This laboratory-scale study validates the effectiveness of SWIR spectroscopy as a prominent tool for pre-concentrating sedimentary copper deposits. It enables the production of a concentrate with a copper content of 1.49% and waste with 0.12%, resulting in an upgrading rate of 43% from the feed, which originally has a copper grade of 1.04%.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"46 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Dust Monitoring in Occupational Environments: A Case Study on Using Low-Cost Dust Monitors for Enhanced Data Collection and Analysis 职业环境中的实时粉尘监测：使用低成本粉尘监测仪加强数据收集和分析的案例研究

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-11 DOI: 10.1007/s42461-024-01039-6

Cody Wolfe, Emanuele Cauda, Milan Yekich, Justin Patts

{"title":"Real-Time Dust Monitoring in Occupational Environments: A Case Study on Using Low-Cost Dust Monitors for Enhanced Data Collection and Analysis","authors":"Cody Wolfe, Emanuele Cauda, Milan Yekich, Justin Patts","doi":"10.1007/s42461-024-01039-6","DOIUrl":"https://doi.org/10.1007/s42461-024-01039-6","url":null,"abstract":"A worker’s personal exposure to respirable dust in occupational environments has traditionally been monitored using established methodologies which entail the collection of an 8-h representative sample that is sent away for laboratory analysis. While these methods are very accurate, they only provide information on the average exposure during a specific time period, generally a worker’s shift. The availability of relatively inexpensive aerosol sensors can allow researchers and practitioners to generate real-time data with unprecedented spatial and temporal granularity. Low-cost dust monitors (LCDM) were developed and marketed for air pollution monitoring and are mostly being used to help communities understand their local and even hyper-local air quality. Most of these integrated sensing packages cost less than $300 per unit, in contrast to wearable or area dust monitors specifically built for mining applications which have been around for decades but still average around $5000 each. At the National Institute for Occupational Safety and Health (NIOSH), we are leveraging the power of high-volume data collection from networks of LCDM to establish baseline respirable hazard levels and to monitor for changes on a seasonal basis as well as following any application of control technologies. We have seen the effective use and advantages of monitoring live data before, during, and after events like shift changes, operational changes, ventilation upgrades, adverse weather events, and machine maintenance. However, many factors have prevented a systematic adoption of LCDMs for exposure monitoring: concern for their analytical performance, the complexity of use, and lack of understanding of their value are some factors. This contribution outlines a 1-year case study at a mine in Wisconsin, USA, covering the installation, maintenance, data visualizations, and collaboration between NIOSH researchers and the industrial hygiene professionals at the mine.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"17 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental and Mechanistic Analysis of Bastnaesite Pelletization in the Context of Carbochlorination 羧基氯化背景下巴斯特奈斯岩颗粒化的实验和机理分析

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-09 DOI: 10.1007/s42461-024-01041-y

Haiyue Xue, Guozhi Lv, Long Wang, Ting-an Zhang

{"title":"Experimental and Mechanistic Analysis of Bastnaesite Pelletization in the Context of Carbochlorination","authors":"Haiyue Xue, Guozhi Lv, Long Wang, Ting-an Zhang","doi":"10.1007/s42461-024-01041-y","DOIUrl":"https://doi.org/10.1007/s42461-024-01041-y","url":null,"abstract":"Rare earth elements, as strategic resources, have garnered global attention. Among these elements, bastnaesite stands out as one of the most abundant rare earth resources. It has various production processes, with carbochlorination being one of the most effective for rare earth recovery. We propose a carbochlorination process for bastnaesite using aluminum chloride produced in situ from alumina, which serves as the fluorine-fixing agent, and coke, which serves as the reducing agent. In the carbochlorination process, to prevent raw material from splashing during the reaction in the packed bed, a binder is typically added, and a reducing agent is used for balling. The impact of various binders on the strength of bastnaesite pellets was investigated, and the bonding mechanisms of the binders were analyzed and discussed. With pellet strength as the primary focus, an experimental investigation was conducted on the factors affecting binder addition, raw material particle size, water addition, and drying temperature. The results indicated that a raw material particle size of 100 mesh, a binder additive amount of 3%, a water addition of 11%, and a drying temperature of 100 ℃ were optimal experimental conditions. Under these conditions, the dry and wet ball drop strengths were 52.5 times and 10.5 times greater, respectively, and the wet and dry compressive strengths were 760.71 N/cm2 and 2.79 N/cm2, respectively. To reduce experimental costs, the composite binder and its doping ratio were explored. Finally, pellets prepared with the three binders were selected for experimental verification of carbochlorination.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"32 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating Pillar Strength for Rock Salt Mines of the Salt Range Pakistan Using Statistical and Artificial Neural Network Modeling Techniques 利用统计和人工神经网络建模技术估算巴基斯坦盐岭岩盐矿的支柱强度

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-08 DOI: 10.1007/s42461-024-01037-8

Y. Majeed, K. M. Sani, M. Z. Emad

{"title":"Estimating Pillar Strength for Rock Salt Mines of the Salt Range Pakistan Using Statistical and Artificial Neural Network Modeling Techniques","authors":"Y. Majeed, K. M. Sani, M. Z. Emad","doi":"10.1007/s42461-024-01037-8","DOIUrl":"https://doi.org/10.1007/s42461-024-01037-8","url":null,"abstract":"This research proposes empirical models to estimate pillar strength by adopting multilinear regression and artificial neural network approaches for rock salt mines of the Salt Range, Punjab, Pakistan. The field data of a total of 168 pillars was collected from three (03) selected rock salt mines being operated by Pakistan Mineral Development Corporation. The field work included geometry of pillars, Schmidt rebound hardness (SRH), uniaxial compressive strength (UCS), fracture spacing, fracture condition, joint-orientation, groundwater state, weathering effects, blasting effects, and mining-induced stress. The dataset collected from the field for each rock salt pillar was further utilized to determine rock quality designation (RQD), rock mass rating (RMR), mining rock mass rating (MRMR), design rock mass strength (DRMS), and pillar strength (({sigma }_{p})). The modeling was done using a dataset of 150 columns, and the remaining data of 18 pillars was left for validation purposes. The proposed ANN and MLR models have R-square (R2) values of 95.35% and 91.61%, respectively. Further, the prediction performance of the ANN model was also compared with that of multilinear regression (MLR). It was found that the ANN model outperformed the MLR model.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"30 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Sustainable Complexation Leaching of Critical Metals from Spent Lithium-Ion Batteries by Glycine in a Neutral Solution 中性溶液中甘氨酸对废锂离子电池中关键金属的可持续络合沥滤作用

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-05 DOI: 10.1007/s42461-024-01040-z

Jiajia Wu, Junmo Ahn, Jaeheon Lee

{"title":"A Sustainable Complexation Leaching of Critical Metals from Spent Lithium-Ion Batteries by Glycine in a Neutral Solution","authors":"Jiajia Wu, Junmo Ahn, Jaeheon Lee","doi":"10.1007/s42461-024-01040-z","DOIUrl":"https://doi.org/10.1007/s42461-024-01040-z","url":null,"abstract":"To reduce the environmental footprint of hydrometallurgical processing of black mass from spent lithium-ion batteries (LIBs), a green leaching system based on glycine and sodium metabisulfite (Gly-SMS) was proposed. The novel leaching system was validated using black mass from end-of-life batteries and manufacturing scrap from battery producers, representing the two dominant black mass types processed in the market. The leaching study demonstrated that the highest cobalt and lithium recoveries of 100% and 99.8% were achieved under optimal conditions. The leaching mechanism revealed that the dissolution of LiCoO2 in the Gly-SMS solution followed the shrinking core model. The apparent activation energies for cobalt and lithium were determined as 48.05 kJ/mol and 41.51 kJ/mol, respectively, indicating a surface chemical reaction controlling mechanism. The leachate was then processed by an acidification-precipitation technique with oxalic acid as the precipitant to remove cobalt. Glycine complexes with metal ions by zwitterionic ligand and recycles in the leaching-precipitation circuit, reducing the reagent cost. Compared to other studies, this leaching system has near-neutral operating conditions and is cost-effective, making it an economically viable alternative for treating cathode materials from spent LIBs.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"78 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining 开发用于地下浅层采矿稀释预测的新型混合智能预测模型

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-05 DOI: 10.1007/s42461-024-01029-8

Prosper Chimunhu, Roohollah Shirani Faradonbeh, Erkan Topal, Mohammad Waqar Ali Asad, Ajak Duany Ajak

{"title":"Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining","authors":"Prosper Chimunhu, Roohollah Shirani Faradonbeh, Erkan Topal, Mohammad Waqar Ali Asad, Ajak Duany Ajak","doi":"10.1007/s42461-024-01029-8","DOIUrl":"https://doi.org/10.1007/s42461-024-01029-8","url":null,"abstract":"Tenuous dilution estimates in underground mine production scheduling continue to cause significant variations between schedule forecasts and actual production. This arises partly from the inference of dilution from predecessor stopes’ performance, disregarding that these stopes would have undergone multiple intermediate design changes between scheduling and actual mining. The resultant drill and blast-influenced dilution factors gradually lose its robustness over longer planning horizons or when applied to greenfield or brownfield expansions that do not have prior performance data. To overcome this problem, a new methodology is proposed to predict dilution in underground sub-level open stoping (SLOS) using basic geological, geotechnical and stope design attributes available in the early stage of mine planning. The method utilises principal component analysis (PCA), classification and regression tree (CART) algorithm and stepwise selection and elimination (SSE) analysis. First, SSE analysis was conducted to identify the most important independent variables to be used with the CART algorithm (i.e., the SSE-CART model) to provide a predictive model. PCA analysis was then performed, and the new principal components were used to propose a new comparative model (i.e., the PCA-CART model). Low R2 values were observed for both models, necessitating the consolidation of dilution categories to increase the models’ prediction bandwidth. The hybrid PCA-CART model outperformed the SSE-CART model with overall F1 score prediction accuracy of 72% and target dilution category prediction accuracy of over 93% against SSE-CART’s 70% and 72%, respectively. Importantly, this study revealed a 13% minimum underestimation of dilution relative to the original design stopes.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"27 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research Status and Prospects of Auto-height Adjustment Strategy for Shearer 剪板机自动调高策略的研究现状与展望

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-03 DOI: 10.1007/s42461-024-01035-w

Yuwei Zhu, Pengfei Wang

{"title":"Research Status and Prospects of Auto-height Adjustment Strategy for Shearer","authors":"Yuwei Zhu, Pengfei Wang","doi":"10.1007/s42461-024-01035-w","DOIUrl":"https://doi.org/10.1007/s42461-024-01035-w","url":null,"abstract":"The development of autonomous shearer height adjustment technology, a crucial component of generalized mining automation, is covered in this study. This study examines the main technical development research in the two directions of coal-rock interface detection and memory cutting in order to investigate the development of shearer auto-height adjustment technology. The development of five methods, such as image recognition method, is introduced in detail in coal rock identification. It lists the shortcomings of each approach and provides an overview of the major variables influencing the advancement of shearer auto-height adjustment technology. Based on the current state of height adjustment technology development and the demand for coal mine intelligence, the following development outlook for auto-height adjustment of shearers is suggested: integrating a variety of cutting-edge technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and Big Data (Big Data), along with the safety mechanism, to create a more complete and effective auto-height adjustment system for shearers. The article concludes by highlighting ongoing research in this area, which uses data expansion to address the issue of poor data quality while also allowing for the combination of machine learning algorithms, data expansion by the appropriate network model to train high-quality and high-precision models, and the development of memory cutting technology to create a comprehensive, continuous, and accurate independent height adjustment control system of the shearer.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"85 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Artificial Intelligence to the Alert of Explosions in Colombian Underground Mines 人工智能在哥伦比亚地下矿井爆炸预警中的应用

IF 1.9 4区工程技术

Mining, Metallurgy & Exploration Pub Date : 2024-07-03 DOI: 10.1007/s42461-024-01008-z

Luis Vallejo-Molina, Astrid Blandon-Montes, Sebastian Lopez, Jorge Molina-Escobar, Andres Ortiz, David Soto, Jose Torero, Alejandro Toro, Alejandro Molina

{"title":"Application of Artificial Intelligence to the Alert of Explosions in Colombian Underground Mines","authors":"Luis Vallejo-Molina, Astrid Blandon-Montes, Sebastian Lopez, Jorge Molina-Escobar, Andres Ortiz, David Soto, Jose Torero, Alejandro Toro, Alejandro Molina","doi":"10.1007/s42461-024-01008-z","DOIUrl":"https://doi.org/10.1007/s42461-024-01008-z","url":null,"abstract":"The use of Artificial Intelligence (AI), particularly of Artificial Neural Networks (ANN), in alerting possible scenarios of methane explosions in Colombian underground mines is illustrated by the analysis of an explosion that killed twelve miners. A combination of geological analysis, a detailed characterization of samples of coal dust and scene evidence, and an analysis with physical modeling tools supported the hypothesis of the existence of an initial methane explosion ignited by an unprotected tool that was followed by a coal dust explosion. The fact that one victim had a portable methane detector at the moment of the methane explosion suggested that the ubiquitous use of these systems in Colombian mines could be used to alert regulatory agencies of a possible methane explosion. This fact was illustrated with the generation of a database of possible readouts of methane concentration based on the recreation of the mine atmosphere before the explosion with Computational Fluid Dynamics (CFD). This database was used to train and test an ANN that included an input layer with two nodes, two hidden layers, each with eight nodes, and an output layer with one node. The inner layers applied a rectified linear unit activation function and the output layer a Sigmoid function. The performance of the ANN algorithm was considered acceptable as it correctly predicted the need for an explosion alert in 971.9 per thousand cases and illustrated how AI can process data that is currently discarded but that can be of importance to alert about methane explosions.","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"13 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0